logo


St. Bartholomew's Hospital, London, UK

New Kafka Adaptive System Saves St Bart's Endocrinology Department 35 "Man Hours" per Week


Background
The Endocrinology Department at St. Barts Hospital, London, is recognised as a worldwide centre of excellence - both for the treatment of endocrinological conditions and for academic research. With over 75 patients per week, the workload is intensive, and therefore reliable computing systems are a pre-requisite for the success of the unit. However, like many departments within NHS trusts, a paper-based Patient Diary, with only rudimentary computer systems to back this up, was the order of the day. In order to improve efficiency and effectiveness, St Barts contracted Kafka Adaptive to develop and implement a computer system that would not only remove the old paper-based diary system, but also add considerable value to the research function.

The Old System
Previously a paper-based Patient Diary system was in place. This had a number of major drawbacks:

· Only one person could access the diary at any one time: with three phone lines coming in to the department, patients were often asked to call back later - simply to make or confirm an appointment;

· Some patients have annual appointments only, therefore if the diary for the New Year was not yet available, appointments would have to written into the rear of the current diary, and then transcribed when the new diary became available. This was both time consuming and wasted effort - with the added danger of transcription errors or lost appointments.

· Ultimately, all diary records had to be input to the computer system - again utilising expensive operator time and running the risk of transcription errors.

Additionally, the existing PC-based system was standalone, meaning remote access was impossible; the application itself had a poor user interface, with no cumulative storage of patient data and no automatic back-up routines; when manual back-ups were initiated, data was archived on floppy disks -an insecure and unreliable media. Another drawback of floppy disk archiving was that complete, cumulative historical patient data could not be retrieved.

To sum up: the old system was cumbersome, prone to data transcription errors and lost data, and unable to add value through providing cumulative historical data. Kafka Adaptive's challenge was to deliver a system that completely replaced the existing processes, and that would add significant value to the research function of the department.

The Kafka Solution

"Because this is a research unit we are asked to change tests on a regular basis - new tests - rennin, for example - this needed one label and one tube and now we do three - we can easily change the labels - previously we would have had to call in an IT support person, and this took time. Also, we couldn't override the system, so if the template was set up to print six labels and we only needed one, then we would have to print six anyway. This was a waste of consumables and time. It's so easy now - such a relief."
Sam Uwasu, Head Nurse, Francis Fraser Ward lab, St Barts

From the start, Kafka Adaptive approached the brief from a data logistics perspective. Patient data needed to be easily input, easily, securely and reliably archived, and easily retrieved - not only in the department, but also remotely, if required.

Kafka's solution comprises a set of wireless-enabled PDAs, linking into a server-based Patient Diary application. By providing each nurse with a PDA, the problem of access to the physical diary was immediately removed. Secondly, as patient data is being input directly to the system, transcription errors are now a thing of the past - as well as having the added benefit of users being immediately prompted if there is a diary clash that would previously have resulted in a double booking.

The Kafka-designed PDA interface has proven to be easy to use, with all staff comfortably using the new system within days of being trained. Additionally, St. Barts estimates that the removal of the need for a data input clerk to transfer the patient data into the PC system is saving at least 35 man hours per week - in other words, a whole person, per week. The cost benefits of such a saving speak for themselves.

Next, department administrators are now able to print out daily workloads for the clinical staff - making life easier for the staff, and greatly assisting in capacity planning on a daily, weekly and monthly basis. Allied to this is the ability for administrative staff to graphically demonstrate activity levels in order to back up funding requests, and researchers can mine data to search for significant trends.

Finally, as each week passes, for the first time in the history of this centre of clinical excellence, cumulative patient data is now becoming available. Ultimately, St Barts intends to make this data available to its counterparts across the UK and worldwide - meaning that endocrinological trends should become apparent earlier.

Kafka Exceeds the Brief
Importantly, however, through meticulous study of the department's data logistics processes during the scoping stage, Kafka not only met the brief in full, but has also added significant extra value to the system. Label generation is now in the hands of the staff, removing the need for external IS personnel to change label templates, or create new ones, and when new Basal test types or revised ICD-10 codes are required, the system is quickly and easily customisable. Training has proven to be minimal for staff to get up-to-speed, and the system is fast, stable and user-friendly. St Barts has already gone on record to state that all Endocrinology departments, inside or outside the NHS, and inside or outside the UK, should invest in the Kafka Adaptive solution.

Data Logistics Proof Points

Real- and near-real time data collection
Real- and near-real time alerts and exception handling
Wireless data delivery
Decrease time gaps between data collection and medical analysis

Products

Kafka Wireless Clinician
Kafka Database Integrators
Kafka Investigator (Management software for protocol and clinical management professionals)
Kafka Application Services Solutions (Hosted solutions